Companies

Dayjob

getdayjob.ai

Dayjob provides AI-powered real-time scheduling for short-haul trucking and waste-management fleets.

HQLondon, Not applicable, United Kingdom
Employees1-50
1 active role
Jobs checked 6h ago
AI / MLAI Agent / AutomationB2B SaaS

About

Dayjob builds AI scheduling agents for short-haul trucking and industrial logistics, initially serving waste-management and recycling operators. Its agent integrates with existing ERP systems and continuously re-optimizes routes in real time, producing fleet schedules in about 60 seconds and delivering reported efficiency and revenue gains.

Market

Dayjob competes in waste-management and industrial-logistics route optimization, dispatch, and fleet-scheduling software. It differentiates by offering a purpose-built AI scheduling agent that sits on top of existing ERP and job systems, continuously re-optimizes routes in real time, and handles waste-specific constraints such as container or skip sizes, stacking rules, driver shifts, time windows, and live changes rather than requiring a rip-and-replace system migration.

Target Customers

Dayjob targets waste-management and short-haul trucking operators, particularly skip, roll-off, and dumpster fleets with multiple drivers and complex daily scheduling. Its primary buyers and users are transport planners, dispatchers, and operations managers who need to automate route planning and respond to live changes.

At a Glance

Problem

Dayjob targets the operational bottleneck in industrial logistics, initially focusing on waste and skip-hire fleets. Scheduling is still built manually each morning: a transport planner may spend 60–90 minutes assigning jobs to trucks, only for the plan to become wrong within hours. Planners must continuously balance vehicle capacity, weight limits, driver hours, customer time windows, travel times and live traffic, while many operators struggle to hire and train enough experienced planners.

The economic pain is substantial: inefficient schedules reduce fleet utilization, increase idle time and fuel costs, cause jobs to be rolled over, and leave revenue-producing capacity unused. Dayjob’s clearest use case is automatically scheduling a waste-hauling fleet so it completes more jobs per truck, meets customer time slots more reliably and responds quickly when conditions change; the company says that adding just 10 jobs per day can be worth millions of pounds annually for a fleet.

Product / Service

Dayjob is an AI scheduling agent delivered as software that sits on top of a customer’s existing job-management or ERP system and connects with vehicle telematics. It pulls in the jobs, driver information and vehicle data, then analyzes millions of possible combinations to produce a full next-day fleet schedule in about 60 seconds rather than requiring a planner to spend most of the morning building one manually.

The system considers travel times, skip or container sizes, driver shifts, stacking rules, customer priorities and time windows. It can also reallocate jobs, reroute drivers and re-plan during the day when cancellations, delays or other changes occur. The value proposition is higher fleet efficiency and revenue, fewer rolled jobs, better on-time performance and less administrative work, while allowing planners to focus on exceptions and operational priorities rather than repetitive scheduling.

Market

Dayjob competes in AI-enabled fleet scheduling, route optimization and broader industrial-logistics operations software. It has chosen waste management as its beachhead because waste-hauling schedules combine high variability, regulatory constraints and constant real-time changes, but the company positions scheduling as the first of several AI agents for the wider industrial-logistics workflow. Its adjacent competitive set includes waste route-optimization products such as OptimoRoute and broader waste-operations platforms such as WasteHero, while Dayjob emphasizes purpose-built scheduling that works with existing ERP systems rather than replacing the operating stack.

The company is not pre-revenue: its latest disclosed YC launch update reported $496K in annual recurring revenue, live UK fleets and a US launch in progress. It also reported 5–10% improvement in fleet efficiency from day one, a 50% improvement in hitting customer time slots and one customer achieving an £800K revenue uplift in its first year. These figures are company-reported early traction rather than independently audited results, but they indicate initial commercial adoption and a measurable ROI story.

Founders & Leadership

George PostlethwaiteFounder
CEO and Co-Founder
Fred FooksFounder
CTO and Co-Founder

Funding History

2026-03
Pre-Seed$1.63M

Playfair Capital, Y Combinator

Recent News

2026-04-23product
Dayjob: AI Agents for Industrial Logistics

Y Combinator highlighted Dayjob’s AI scheduling agent for waste trucks and industrial logistics. The agent builds a full fleet schedule in about 60 seconds on top of existing ERP software; the company said it was live in the UK and launching in the US.

2026-01-30partnership
VWS Partners with AI Scheduling Tool Dayjob

VWS Software Solutions announced a collaboration with Dayjob to provide waste and recycling operators with greater control, flexibility, and visibility over their schedules.

2026-01-27partnership
How Coastal Recycling is using AI to transform operations

Coastal Recycling described how Dayjob adds automated, AI-driven vehicle scheduling to its operations. The integration sits directly inside Coastal’s PurGo workflow.

Active Roles

1
Austin/Sales/8d ago

Business Model

Dayjob sells B2B AI scheduling software to waste-management and other short-haul fleet operators, with public evidence indicating ROI-based pricing. The available materials do not disclose a fixed subscription, per-vehicle price, or other detailed pricing schedule.

Products

AI scheduling agent for waste and short-haul fleetsDynamic route planning and in-day re-planningERP/job-system and telematics integrationsScheduling-performance and driver-performance insights

Customers

No publicly named enterprise customers or customer logos identified in the available evidence.

Tech Stack

AI/ML scheduling and route optimizationReal-time constraint-based re-optimizationERP and job-management system integrationsTelematics/GPS integrationsContinual learning from operational data

Competitors

AMCS
Routeware
SmartRoutes
SkipRoute
Route4Me
OptimoRoute